Devices Price Classification System

This repository contains a Jupyter Notebook for a device price classification system. The goal of this system is to classify devices into different price categories based on their features.

Table of Contents

• Project Overview
• Installation
• Usage
• Data
• Model Training and Evaluation
• Results
• Contributing
• License

Project Overview

This project focuses on classifying electronic devices into different price ranges using machine learning techniques. The notebook provides a comprehensive walkthrough from data loading and preprocessing to model training, evaluation, and results visualization.

Installation

To run the notebook, you need to have Python and Jupyter Notebook installed. You also need to install the required Python packages. The necessary packages include:

• pandas
• numpy
• scikit-learn
• matplotlib
• seaborn

Usage

To use the notebook, follow these steps:

1. Clone this repository:

   git clone https://github.com/YousryEssam/Devices-Price-Classification-System.git

2. Navigate to the cloned repository:

   cd Devices-Price-Classification-System

3. Open the Jupyter Notebook:

   jupyter notebook Devices_Price_Classification_System.ipynb

Data

The dataset used for this project should be loaded in the notebook. Ensure that your data file is in the correct directory or update the file path in the notebook accordingly.

Model Training and Evaluation

The notebook includes steps for:

• Data loading and preprocessing
• Feature engineering
• Splitting the data into training and testing sets
• Training different machine learning models
• Evaluating model performance using various metrics
• Hyperparameter tuning

Results

The results section of the notebook provides insights into the model's performance. This includes accuracy, confusion matrix, and other relevant metrics. Visualizations such as feature importance and ROC curves may also be included.

Contributing

Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please create an issue or submit a pull request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/fooBar)
3. Commit your changes (git commit -am 'Add some fooBar')
4. Push to the branch (git push origin feature/fooBar)
5. Create a new Pull Request

License

This project is licensed under the MIT License. See the LICENSE file for details.